Células solares fotovoltaicas : desarrollo de sistemas de monitorización y seguimiento de sistemas fotovoltaicos

En la UMA se investiga tanto el control y análisis de este tipo de dispositivos, como en las características eléctricas de módulos de distintas tecnologías que ayudan, entre otras cosas, a conocer enn directo indicadores como la producción real de energía de estas plataformas

Models for the Optimization and Evaluation of Photovoltaic Self-Consumption Facilities

The results obtained for the modeling and optimization of photovoltaic self-consumption facilities are presented. The study has been carried out for three Spanish cities with different climatic conditions. The self-consumption and self-sufficiency curves for different hourly consumption profiles have been obtained based on the installed peak power and the size of the battery. Different models of machine learning are proposed to predict these parameters. The input variables of these models are related to the configuration of the installation, its location and the type of consumption profile. The model with best predictions of self-sufficiency is Random Forest, which in cross-validation has a relative error of 5%. For the prediction of self-consumption, the model that performs best is the multilayer perceptron, with an average absolute error of 0.55 and an absolute relative error of 3%

Characterisation of hourly temperature of a thin-film module from weather conditions by artificial intelligence techniques

The aim of this paper is the use and validation of artificial intelligence techniques to predict the temperature of a thin-film module based on tandem CdS/CdTe technology. The cell temperature of a module is usually tens of degrees above the air temperature, so that the greater the intensity of the received radiation, the greater the difference between these two temperature values. In practice, directly measuring the cell temperature is very complicated, since cells are encapsulated between insulation materials that do not allow direct access. In the literature there are several equations to obtain the cell temperature from the external conditions. However, these models use some coefficients which do not appear in the specification sheets and must be estimated experimentally. In this work, a support vector machine and a multilayer perceptron are proposed as alternative models to predict the cell temperature of a module. These methods allow us to achieve an automatic way to learn only from the underlying information extracted from the measured data, without proposing any previous equation. These proposed methods were validated through an experimental campaign of measurements. From the obtained results, it can be concluded that the proposed models can predict the cell temperature of a module with an error less than 1.5 °C.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

New software tool to characterize photovoltaic modules from commercial equipment

A software platform has been developed in order to unify the different measurements obtained from different manufacturers in the photovoltaic system laboratory of the University of Malaga, Spain. These measurements include the current-voltage curve of PV modules and several meteorological parameters such as global and direct irradiance, temperature and spectral distribution of solar irradiance. The measurements are performed in an automated way by a stand-alone application that is able to communicate with a pair of multimeters and a bipolar power supply that are controlled in order to obtain the current–voltage pairs. In addition, several magnitudes, that can be configured by the user, such as irradiance, module temperature or wind speed, are incorporated to register the conditions of each measurement. Moreover, it is possible to attach to each curve the spectral distribution of the solar radiation at each moment. Independently of the source of the information, all these measurements are stored in a uniform relational database. These data can be accessed through a public web site that can generate several graphics from the data.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. Junta de Andalucía. Proyecto de Excelencia P11-RNM-711

Optimization of Energy Distribution in Solar Panel Array Configurations by Graph Theory and Minkowski’s Paths

Nowadays, the development of the photovoltaic (PV) technology is consolidated as a source of renewable energy. The research in the topic of maximum improvement on the energy efficiency of the PV plants is today a major challenge. The main requirement for this purpose is to know the performance of each of the PV modules that integrate the PV field in real time. In this respect, a PLC communications based Smart Monitoring and Communications Module, which is able to monitor at PV level their operating parameters, has been developed at the University of Malaga. With this device you can check if any of the panels is suffering any type of overriding performance, due to a malfunction or partial shadowing of its surface. Since these fluctuations in electricity production from a single panel affect the overall sum of all panels that conform a string, it is necessary to isolate the problem and modify the routes of energy through alternative paths in case of PV panels array configuration.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Barrios zero como germen de ciudades sin emisiones.

El trascurso del siglo XX está íntimamente relacionado con el nacimiento y auge de las metrópolis contemporáneas. Durante este siglo, el desarrollo de la humanidad se relaciona íntimamente al desarrollo y crecimiento de las ciudades Hoy en día, el 55% de la población mundial vive en áreas urbanas, una proporción que se espera que aumente al 68% para 2050. De alguna manera, las ciudades se distancian de ser un problema para convertirse en una parte fundamental de la solución. Cuanto más se actúa de manera local, más fácil es involucrar a vecinos, empresas y administraciones, porque solamente desde esta acción conjunta se pueden definir vías de trabajo eficientes en la mejora de las ciudades y en el desarrollo sostenible de los territorios. En este proyecto hemos querido conocer en un caso real, cual es el consumo energético y que acciones deberían tomarse para que fuera un barrio cero emisiones, bajo la hipótesis de que el planteamiento de las actuaciones de revitalización de barrios y su sostenibilidad energética se deben hacer desde el esfuerzo comunitario, partiendo de la reflexión sobre la creación de distritos de energía casi nula basados en una economía baja en carbono, como un proceso en el que los vecinos estén concienciados de que la mitigación del cambio climático parte de la voluntad de ellos mismos para la modificación de sus hábitos de consumo, la gestión de la demanda energética y en el conocimiento de los factores que hacen más sostenible el futuro de las ciudades. Hemos evaluado a modo de proyecto piloto, un barrio de Málaga, con el fin de establecer las acciones para convertir el barrio en un espacio libre de emisiones, estableciendo una metodología propia, que parte de los consumos de los barrios, lo relaciona con las posibles acciones vinculadas, así como sus consecuencias en las posibles mejoras de la sostenibilidad energética urbana

Analysis of the degradation of amorphous silicon-based modules after 11 years of exposure by means of IEC60891:2021 procedure 3

The degradation of two amorphous silicon-based photovoltaic (PV) modules, namely, of single junction amorphous silicon (a-Si) and of micromorph tandem (a-Si/μ-Si), after 11 years of exposure in the south of Spain is analyzed. Their I-V curves were measured outdoors to study the changes of the electrical parameters in the course of three different periods: during the initial days of exposure, during the first year, and in the subsequent 10-year period. The translation of the curves to an identical set of operating conditions, which enables a meaningful comparison, was done by the dif ferent correction procedures described in the standard IEC60891:2021, including the procedure 3, which does not require the knowledge of module parameters, whose values are typically not available. The annual power degradation rates over the entire 11-year period are 1.12% for the a-Si module, which is 3.02% for the first year, and 0.98% for the a-Si/μ-Si, which is 2.29% for the initial yearThis work is supported by Ministero dell'Istruzione, dell'Università e della Ricerca (Italy) (grant PRIN2020-HOTSPHOT 2020LB9TBC and grant PRIN2017-HEROGRIDS 2017WA5ZT3_003); Università degli Studi di Salerno (FARB funds); Ministerio de Ciencia, Innovacion y Universidades (Spain) (grant RTI2018-095097-B-I0)

Scalable method for administration of resource technologies under stochastic procedures

During the development of the S3Unica project (Smart Specialisation University Campus) and its application in the ASSET project (Advanced Systems Studies for Energy Transition), both within the European Commission, the resolution of the distributed energy generation model was proposed through the creation of an algorithm that would allow the shared market between producers and consumers. From this premise arose the need to create a replicable system to resolve this situation in the new shared generation environment, using low-cost technologies. This work develops the scalable method for resource management technologies (SMART), based on stochastic procedures, which generates microgrids with an integrated energy market. The interest of this work is based on the incorporation of real-time analysis, applying stochastic methods, and its fusion with probabilistic predictive methods that evolve and harmonise the results. The fact that the process is self-learning also enables the use of metadomotic as a tool for both comfort improvement and energy sharing. The most important results developed were the design of the internal scheme of the low-cost SMART control device together with the developments of both individual and collective resolution algorithms. By achieving the incorporation of internal and external producers in the same numerical procedure, the distributed and hybrid generation models are solved simultaneously.We thank the support of this paper from University of Malaga and CBUA (funding for open access charge: Universidad de Málaga / CBUA) and we thank also the anonymous reviewers whose suggestions helped improve and clarify this manuscript. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors